The architecture of scene understanding module is presented in REF . Similar to non-local block [1]}, it first uses \(1 \times 1\)  convolutions to transform the input features \(\mathbf {X} \in R^{N \times C_{f}}\)  into query,key and value results represented by \(\mathbf {Q} \in R^{N \times C_{q}}\) , \(\mathbf {K} \in R^{N \times C_{k}}\)  and \(\mathbf {V} \in R^{N \times C_{v}}\)  respectively, where \(N=H \times W\)  is the resolution. Then the predicted attention map \(\tilde{\mathbf {A}}\)  can be obtained with
\(\tilde{\mathbf {A}}=Sigmoid(\mathbf {Q}^{T}\mathbf {K}),\) 
